Exploring the use of concept spaces to improve medical information retrieval

Persistent Link:
http://hdl.handle.net/10150/106253
Title:
Exploring the use of concept spaces to improve medical information retrieval
Author:
Houston, Andrea L.; Chen, Hsinchun; Schatz, Bruce R.; Hubbard, Susan M.; Sewell, Robin R.; Ng, Tobun Dorbin
Citation:
Exploring the use of concept spaces to improve medical information retrieval 2000, 30:171-186 Decision Support Systems
Publisher:
Elsevier
Journal:
Decision Support Systems
Issue Date:
2000
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/106253
Submitted date:
2004-08-13
Abstract:
This research investigated the application of techniques successfully used in previous information retrieval research, to the more challenging area of medical informatics. It was performed on a biomedical document collection testbed, CANCERLIT, provided by the National Cancer Institute (NCI) , which contains information on all types of cancer therapy. The quality or usefulness of terms suggested by three different thesauri, one based on MeSH terms, one based solely on terms from the document collection, and one based on the Unified Medical Language System UMLS Metathesaurus, was explored with the ultimate goal of improving CANCERLIT information search and retrieval. Researchers affiliated with the University of Arizona Cancer Center evaluated lists of related terms suggested by different thesauri for 12 different directed searches in the CANCERLIT testbed. The preliminary results indicated that among the thesauri, there were no statistically significant differences in either term recall or precision. Surprisingly, there was almost no overlap of relevant terms suggested by the different thesauri for a given search. This suggests that recall could be significantly improved by using a combined thesaurus approach.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Evaluation; Medical Libraries; Digital Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial Intelligence lab; AI lab; Information retrieval; Medical informatics; Medical information retrieval; Concept space; MeSH terms; UMLS Metathesaurus

Full metadata record

DC FieldValue Language
dc.contributor.authorHouston, Andrea L.en_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorSchatz, Bruce R.en_US
dc.contributor.authorHubbard, Susan M.en_US
dc.contributor.authorSewell, Robin R.en_US
dc.contributor.authorNg, Tobun Dorbinen_US
dc.date.accessioned2004-08-13T00:00:01Z-
dc.date.available2010-06-18T23:43:17Z-
dc.date.issued2000en_US
dc.date.submitted2004-08-13en_US
dc.identifier.citationExploring the use of concept spaces to improve medical information retrieval 2000, 30:171-186 Decision Support Systemsen_US
dc.identifier.urihttp://hdl.handle.net/10150/106253-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThis research investigated the application of techniques successfully used in previous information retrieval research, to the more challenging area of medical informatics. It was performed on a biomedical document collection testbed, CANCERLIT, provided by the National Cancer Institute (NCI) , which contains information on all types of cancer therapy. The quality or usefulness of terms suggested by three different thesauri, one based on MeSH terms, one based solely on terms from the document collection, and one based on the Unified Medical Language System UMLS Metathesaurus, was explored with the ultimate goal of improving CANCERLIT information search and retrieval. Researchers affiliated with the University of Arizona Cancer Center evaluated lists of related terms suggested by different thesauri for 12 different directed searches in the CANCERLIT testbed. The preliminary results indicated that among the thesauri, there were no statistically significant differences in either term recall or precision. Surprisingly, there was almost no overlap of relevant terms suggested by the different thesauri for a given search. This suggests that recall could be significantly improved by using a combined thesaurus approach.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectEvaluationen_US
dc.subjectMedical Librariesen_US
dc.subjectDigital Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial Intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherInformation retrievalen_US
dc.subject.otherMedical informaticsen_US
dc.subject.otherMedical information retrievalen_US
dc.subject.otherConcept spaceen_US
dc.subject.otherMeSH termsen_US
dc.subject.otherUMLS Metathesaurusen_US
dc.titleExploring the use of concept spaces to improve medical information retrievalen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalDecision Support Systemsen_US
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